Identification of Carcass and Meat Quality QTL in an F2 Duroc × Pietrain Pig Resource Population Using Different Least-Squares Analysis Models

A three-generation resource population was constructed by crossing pigs from the Duroc and Pietrain breeds. In this study, 954 F2 animals were used to identify quantitative trait loci (QTL) affecting carcass and meat quality traits. Based on results of the first scan analyzed with a line-cross (LC) model using 124 microsatellite markers and 510 F2 animals, 9 chromosomes were selected for genotyping of additional markers. Twenty additional markers were genotyped for 954 F2 animals and 20 markers used in the first scan were genotyped for 444 additional F2 animals. Three different Mendelian models using least-squares for QTL analysis were applied for the second scan: a LC model, a half-sib (HS) model, and a combined LC and HS model. Significance thresholds were determined by false discovery rate (FDR). In total, 50 QTL using the LC model, 38 QTL using the HS model, and 3 additional QTL using the combined LC and HS model were identified (q < 0.05). The LC and HS models revealed strong evidence for QTL regions on SSC6 for carcass traits (e.g., 10th-rib backfat; q < 0.0001) and on SSC15 for meat quality traits (e.g., tenderness, color, pH; q < 0.01), respectively. QTL for pH (SSC3), dressing percent (SSC7), marbling score and moisture percent (SSC12), CIE a* (SSC16), and carcass length and spareribs weight (SSC18) were also significant (q < 0.01). Additional marker and animal genotypes increased the statistical power for QTL detection, and applying different analysis models allowed confirmation of QTL and detection of new QTL

Application of alternative models to identify QTL for growth traits in an F2 Duroc x Pietrain pig resource population

<p>Abstract</p> <p>Background</p> <p>A variety of analysis approaches have been applied to detect quantitative trait loci (QTL) in experimental populations. The initial genome scan of our Duroc x Pietrain F₂resource population included 510 F₂animals genotyped with 124 microsatellite markers and analyzed using a line-cross model. For the second scan, 20 additional markers on 9 chromosomes were genotyped for 954 F₂animals and 20 markers used in the first scan were genotyped for 444 additional F₂animals. Three least-squares Mendelian models for QTL analysis were applied for the second scan: a line-cross model, a half-sib model, and a combined line-cross and half-sib model.</p> <p>Results</p> <p>In total, 26 QTL using the line-cross model, 12 QTL using the half-sib model and 3 additional QTL using the combined line-cross and half-sib model were detected for growth traits with a 5% false discovery rate (FDR) significance level. In the line-cross analysis, highly significant QTL for fat deposition at 10-, 13-, 16-, 19-, and 22-wk of age were detected on SSC6. In the half-sib analysis, a QTL for loin muscle area at 19-wk of age was detected on SSC7 and QTL for 10th-rib backfat at 19- and 22-wk of age were detected on SSC15.</p> <p>Conclusions</p> <p>Additional markers and animals contributed to reduce the confidence intervals and increase the test statistics for QTL detection. Different models allowed detection of new QTL which indicated differing frequencies for alternative alleles in parental breeds.</p

Iron deposition is independent of cellular inflammation in a cerebral model of multiple sclerosis

<p>Abstract</p> <p>Background</p> <p>Perivenular inflammation is a common early pathological feature in multiple sclerosis (MS). A recent hypothesis stated that CNS inflammation is induced by perivenular iron deposits that occur in response to altered blood flow in MS subjects. In order to evaluate this hypothesis, an animal model was developed, called cerebral experimental autoimmune encephalomyelitis (cEAE), which presents with CNS perivascular iron deposits. This model was used to investigate the relationship of iron deposition to inflammation.</p> <p>Methods</p> <p>In order to generate cEAE, mice were given an encephalitogen injection followed by a stereotactic intracerebral injection of TNF-α and IFN-γ. Control animals received encephalitogen followed by an intracerebral injection of saline, or no encephalitogen plus an intracerebral injection of saline or cytokines. Laser Doppler was used to measure cerebral blood flow. MRI and iron histochemistry were used to localize iron deposits. Additional histological procedures were used to localize inflammatory cell infiltrates, microgliosis and astrogliosis.</p> <p>Results</p> <p>Doppler analysis revealed that cEAE mice had a reduction in cerebral blood flow compared to controls. MRI revealed T2 hypointense areas in cEAE animals that spatially correlated with iron deposition around vessels and at some sites of inflammation as detected by iron histochemistry. Vessels with associated iron deposits were distributed across both hemispheres. Mice with cEAE had more iron-labeled vessels compared to controls, but these vessels were not commonly associated with inflammatory cell infiltrates. Some iron-laden vessels had associated microgliosis that was above the background microglial response, and iron deposits were observed within reactive microglia. Vessels with associated astrogliosis were more commonly observed without colocalization of iron deposits.</p> <p>Conclusion</p> <p>The findings indicate that iron deposition around vessels can occur independently of inflammation providing evidence against the hypothesis that iron deposits account for inflammatory cell infiltrates observed in MS.</p

A Deep Sequencing Approach to Comparatively Analyze the Transcriptome of Lifecycle Stages of the Filarial Worm, Brugia malayi

Lymphatic filariasis, also known as elephantiasis, is a tropical disease affecting over 120 million people worldwide. More than 40 million people live with painful, disfiguring symptoms that can cause severe debilitation and social stigma. The disease is caused by infection with thread-like filarial nematodes (roundworms) that have a complex parasitic lifecycle involving both human and mosquito hosts. In the study, the authors profiled the transcriptome (the set of genes transcribed into messenger RNA rather than all of those in the genome) of the human filarial worm Brugia malayi in different lifecyle stages using deep sequencing technology. The analysis revealed major transitions in RNA expression from eggs through larval stages to adults. Using statistical approaches, the authors identified groups of genes with distinct life stage dependent transcriptional patterns, with particular emphasis on genes displaying sex-biased or germline-enriched patterns and those displaying significant changes during larval development. This study presents a first comprehensive analysis of the lifecycle transcriptome of B. malayi, providing fundamental molecular information that should help researchers better understand parasite biology and could provide clues for the development of more effective interventions

A Pilot Study Identifying Statin Nonadherence With Visit-to-Visit Variability of Low-Density Lipoprotein Cholesterol

Nonadherence to cardiovascular medications such as statins is a common, important problem. Clinicians currently rely on intuition to identify medication nonadherence. The visit-to-visit variability (VVV) of low-density lipoprotein (LDL) cholesterol might represent an opportunity to identify statin nonadherence with greater accuracy. We examined the clinical and pharmacy data from 782 members of the Boston Medical Center Health Plan, seen at either the Boston Medical Center or its affiliated community health centers, who were taking statins and had ≥3 LDL cholesterol measurements from 2008 to 2011. The LDL cholesterol VVV (defined by the within-patient SD) was categorized into quintiles. Multivariate logistic regression models were generated with statin nonadherence (defined by the standard 80% pharmacy refill-based medication possession ratio threshold) as the dependent variable. The proportion of statin nonadherence increased across the quintiles of LDL cholesterol VVV (64.3%, 71.2%, 89.2%, 92.3%, 91.7%). Higher quintiles of LDL cholesterol VVV had a strong positive association with statin nonadherence, with an adjusted odds ratio of 3.4 (95% confidence interval 1.7 to 7.1) in the highest versus lowest quintile of LDL cholesterol VVV. The age- and gender-adjusted model had poor discrimination (C-statistic 0.62, 95% confidence interval 0.57 to 0.67), but the final adjusted model (age, gender, race, mean LDL cholesterol) demonstrated good discrimination (C-statistic 0.75, 95% confidence interval 0.71 to 0.79) between the adherent and nonadherent patients. In conclusion, the VVV of LDL cholesterol demonstrated a strong association with statin nonadherence in a clinic setting. Furthermore, a VVV of LDL cholesterol-based model had good discrimination characteristics for statin nonadherence. Research is needed to validate and generalize these findings to other populations and biomarkers

Key Variants via the Alzheimer\u27s Disease Sequencing Project Whole Genome Sequence Data

INTRODUCTION: Genome-wide association studies (GWAS) have identified loci associated with Alzheimer\u27s disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci. METHODS: We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases = 2184, N controls = 2383) and targeted analyses in subpopulations using WGS data from the Alzheimer\u27s Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants. RESULTS: Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses. DISCUSSION: This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS

Pretreatment HLADQA1-HLADRB1 Testing for the Prevention of Azathioprine-Induced Pancreatitis in Inflammatory Bowel Disease: A Prospective Cohort Study

INTRODUCTION:Azathioprine-induced pancreatitis is an idiosyncratic and unpredictable response, occurring in up to 7% of azathioprine-exposed patients with inflammatory bowel disease (IBD). The haplotype HLADQA1-HLADRB1*07:01A\u3eC is strongly associated with azathioprine-induced pancreatitis in IBD. We aimed to evaluate whether pretreatment HLADQA1-HLADRB1*07:01A\u3eC screening will reduce the risk of azathioprine-induced pancreatitis.METHODS:Participants with IBD were screened for HLADQA1-HLADRB1*07:01A\u3eC, and participants with a variant genotype were excluded from azathioprine treatment. Wild-type participants were started on azathioprine and followed for 3 months. The incidence of pancreatitis was compared with unscreened historical controls.RESULTS:HLADQA1-HLADRB1*07:01A\u3eC screening resulted in an 11-fold reduction in the incidence of azathioprine-induced pancreatitis (n = 1/328 or 0.30% vs n = 13/373 or 3.4%). In propensity score-matched cohorts (age and sex), HLA DQA1-HLADRB1*07:01A\u3eC screening was significantly associated with a reduction in the incidence of AZA-induced pancreatitis independent of weight, glucocorticoid exposure, and smoking status (adjusted odds ratio = 0.075, 95% confidence interval = 0.01-0.58, P = 0.01). Up to 45% (n = 271/599) of participants were excluded from azathioprine therapy based on the haplotype in the HLADQA1-HLADRB1*07:01A\u3eC-screened cohort.DISCUSSION:HLADQA1-HLADRB1*07:01A\u3eC screening reduced the risk of azathioprine-induced pancreatitis; however, using this strategy to guide the use of azathioprine therapy in IBD may eliminate a large proportion of patients from being eligible for treatment with azathioprine. In regions where there is access to other IBD therapies, and given the short-term and long-term toxicities associated with azathioprine, HLADQA1-HLADRB1*07:01A\u3eC-screening may be a clinically relevant strategy for enhancing the safe use of azathioprine in IBD. In addition, cost-effectiveness analyses are needed to further solidify the utility of HLADQA1-HLADRB1*07:01A\u3eC screening in IBD populations

Comprehensive extraction method integrated with NMR metabolomics: a new bioactivity screening method for plants, adenosine A1 receptor binding compounds in Orthosiphon stamineus benth

A large number of plant metabolites has provided as an incomparable chemical source for drug development. However, the wide range of the polarity of metabolites has been a big obstacle for full use of the chemical diversity. The initial step conventional extraction method by a single solvent does not make use of all the metabolites contained in plants. Also, it takes a long time to confirm the target activity of a single compound because of tedious separation steps. To solve the problem, a new extraction method coupled to NMR-based metabolomics is applied to identify bioactive natural products. A comprehensive extraction method consisting of a continuous flow of solvent mixtures through plant material was developed to provide extracts with a wider chemical variety than those yielded with a single solvent extraction. As the model experiment, 1H NMR spectra of the extracts obtained from the comprehensive extraction of Orthosiphon stamineus were subjected to multivariate data analysis to find its adenosine A1 binding activity. On the basis of the results, two flavonoids from a large number of chemicals were clearly verified to show the adenosine A1 binding activity without any further purification steps. This method could provide a solution to the major drawbacks of natural products in drug development

Racial/ethnic differences in job loss for women with breast cancer

IntroductionWe examined race/ethnic differences in treatment-related job loss and the financial impact of treatment-related job loss, in a population-based sample of women diagnosed with breast cancer.MethodsThree thousand two hundred fifty two women with non-metastatic breast cancer diagnosed (August 2005-February 2007) within the Los Angeles County and Detroit Metropolitan Surveillance Epidemiology and End Results registries, were identified and asked to complete a survey (mean time from diagnosis = 8.9&nbsp;months). Latina and African American women were over-sampled (n = 2268, eligible response rate 72.1%).ResultsOne thousand one hundred eleven women (69.6%) of working age (&lt;65&nbsp;years) were working for pay at time of diagnosis. Of these women, 10.4% (24.1% Latina, 10.1% African American, 6.9% White, p &lt; 0.001) reported that they lost or quit their job since diagnosis due to breast cancer or its treatment (defined as job loss). Latina women were more likely to experience job loss compared to White women (OR = 2.0, p = 0.013)), independent of sociodemographic factors. There were no significant differences in job loss between African American and White women, independent of sociodemographic factors. Additional adjustments for clinical and treatment factors revealed a significant interaction between race/ethnicity and chemotherapy (p = 0.007). Among women who received chemotherapy, Latina women were more likely to lose their job compared to White women (OR = 3.2, p &lt; 0.001), however, there were no significant differences between Latina and White women among those who did not receive chemotherapy. Women who lost their job were more likely to experience financial strain (e.g. difficulty paying bills 27% vs. 11%, p &lt; 0.001).ConclusionJob loss is a serious consequence of treatment for women with breast cancer. Clinicians and staff need to be aware of aspects of treatment course that place women at higher risk for job loss, especially ethnic minorities receiving chemotherapy